Mathematical modelling of COVID-19 mortality in China - Marín Machuca, Olegario (2020)
The objective of the work was to develop a mathematical model to analyze the behavior of mortality in the People’s Republic of China caused by COVID-2019. The logistic model was applied to the data reported in Table 1, between January 11 and April 12, 2020. The model formulated was linearized and presented in two forms, which, with the same value of B, introducing a correction factor for the independent variable, t, which serves as “period” and applying the method of minimum squares, the parameters A, k and r were determined, obtaining the respective model (Equation 10), which was analyzed with Pearson’s correlation coefficient, obtaining the correlation coefficient r=-0.9668 and the determination coefficient r^2×100=93.48 %; deducing the best estimate of the model to the process in modeling (Equation 10) to analyze the mortality phenomenon. Likewise, the mortality rate was evaluated, deriving, ordinarily, the best model (Equation 10), obtaining the speed model (Equation 11); describing the best behavior, determining that the maximum mortality rate was 118 persons/day, an event that occurred on 24 February 2020.